An applicant tracking system does not read your CV. It parses it: pulls the text out of the file and tries to sort it into fields — name, contact details, each job with its title and dates, education, skills. Recruiters then search and filter those fields. Everything that follows is about whether the parse works.[1]
Columns and tables
A parser reads text in the order the file stores it, which for a two-column layout is often left column top to bottom, then right column — or worse, line by line across both. Your job title lands next to a skill; your dates attach to the wrong role. The CV looks fine on screen and arrives as noise.[2]
Tables are the same problem with borders. Many CV templates use an invisible table to line up dates on the left and roles on the right; parsers see the cells, not the alignment.
Headings a parser cannot name
Parsers look for section headings they know: Experience, Employment, Work History, Education, Skills. “My Journey”, “Where I’ve Been” and “Toolbox” are headings for a human, and a parser that cannot classify a section may drop it or file it under the previous one.
The fix costs you nothing: use the ordinary words. You can be interesting inside the sections.
Text that isn’t text
Contact details in a header image. A name set as a logo. Skills as icons. Anything the file stores as a picture is invisible to a parser — and a CV with no email address in the text is a CV nobody can reply to.
The same goes for text boxes and shapes in Word: some export as text, some do not, and you will not know which until it fails.
Dates it cannot read
“2019 – present”, “Mar 2019–”, “2019-2021”, “since 2019”. A parser needs to work out how long you did each job, and mixed formats make it guess. Pick one format and use it everywhere. Month and year is enough.
Fonts, PDFs and one more trap
A PDF exported from a design tool sometimes stores each line as a separate object with no reading order, and occasionally stores text as outlines — shapes, not letters. Export from Word, Google Docs or a CV editor instead, and check the result by selecting all the text in the PDF and pasting it somewhere plain. If what you see is your CV in order, a parser will see it too.
What this check does
It reads your CV the way a parser would, then the way a recruiter would. The review leads with structure: which sections it could name, whether every role has readable dates, whether the contact block is text, and what — columns, tables, images — is in the way. Then the wording findings follow, because a CV that parses perfectly and says nothing is still not getting the interview.
When you open the CV in the editor it is already in a one-column template. Change the template as you like; every one here parses.